Practical Strategies for Integrating a Conversation Analyst in an Iterative Design Process

We present a case study of an iterative design process that includes a conversation analyst. We discuss potential benefits of conversation analysis for design, and we describe our strategies for integrating the conversation analyst in the design process. Since the analyst on our team had no previous exposure to design or engineering, and none of the other members of our team had any experience with conversation analysis, we needed to build a foundation for our interaction. One of our key strategies was to pair the conversation analyst with a designer in a highly interactive collaboration. Our tactics have been effective on our project, leading to valuable results that we believe we could not have obtained using another method. We hope that this paper can serve as a practical guide to those interested in establishing a productive and efficient working relationship between a conversation analyst and the other members of a design team.Comment: 11 page

Supporting ethnographic studies of ubiquitous computing in the wild

Ethnography has become a staple feature of IT research over the last twenty years, shaping our understanding of the social character of computing systems and informing their design in a wide variety of settings. The emergence of ubiquitous computing raises new challenges for ethnography however, distributing interaction across a burgeoning array of small, mobile devices and online environments which exploit invisible sensing systems. Understanding interaction requires ethnographers to reconcile interactions that are, for example, distributed across devices on the street with online interactions in order to assemble coherent understandings of the social character and purchase of ubiquitous computing systems. We draw upon four recent studies to show how ethnographers are replaying system recordings of interaction alongside existing resources such as video recordings to do this and identify key challenges that need to be met to support ethnographic study of ubiquitous computing in the wild

Sort and Sift, Think and Shift: Let the Data Be Your Guide An Applied Approach to Working With, Learning From, and Privileging Qualitative Data

The Sort and Sift, Think and Shift qualitative data analysis approach is an iterative process where analysts dive into data to understand its content, dimensions, and properties, and then step back to assess what they have learned and to determine next steps. Researchers move from establishing an understanding of what is in the data (“Diving In”) to exploring their relationship to the data (“Stepping Back”). This process of “Diving In” and “Stepping Back” is repeated throughout analysis. To conclude, researchers arrive at an evidence-based meeting point that is a hybrid story of data content and researcher knowledge. To illustrate core tenets of Sort and Sift, Think and Shift, we analyzed three focus group transcripts from a study of postnatal care referral behavior by traditional birth attendants in Nigeria; these transcripts came from Syracuse University’s Qualitative Data Repository and were unfamiliar to the analytic team prior to this exercise. We focused on letting the data be our guide into not only the explicit purpose of the interviews, but also into the unexpected discoveries that arise when inquiring about people’s lived experiences. Situating our efforts within an Initial Learning Period, each member of the team closely read each transcript, and then identified powerful quotations that made us pause and take note. We documented what we learned from each transcript in an episode profile which contained diagrams and memos. Episode profiles were shared and discussed across the team to identify key points of interest, such as the role of faith in women’s decision-making processes related to their pregnancy and delivery preferences, and concepts of who bears what knowledge about reproductive health. Our engagement in this analytic exercise demonstrates the applicability of qualitative inquiry and Sort and Sift as flexible approaches for applied research

Revisiting the role of the grounded theory research methodology in the accounting Information systems

The aim of this paper is to explore the role of grounded theory (GT) as a research method in the accounting information systems. The GT research method can able the GT researcher to generate a rigour theory. This research paper seeks to investigate how researchers can use GT in relation to its epistemological perspective, methodological stance and research methods. GT as a research philosophy provides clear understanding of how to generate and develop rigorous theory. GT offers an interpretative perspective based on its epistemological stance. This interpretative perspective can be a foundation for GT researchers in interpretative accounting information systems researches

UX design in agile: a DSDM case study

Integrating User Experience (UX) design with agile development continues to be the subject of academic studies and practitioner discussions. Most of the existing literature focuses on SCRUM and XP, but in this paper we investigate a technical company who use DSDM. Unlike other agile methods, DSDM provides a configurable framework and a set of roles that covers the whole software development process. While elements of the UX design integration experience were similar to those reported with other agile methods, working practices to mitigate the challenges were identified using DSDM’s standard elements. Specifically, communication challenges were mitigated by extending two of DSDM’s standard roles. In addition, a change of focus between a design-led phase and a development-led phase of the project changed the communication challenges. Agile teams need to be aware that this change of focus can happen and the implications that it has for their work

Pragmatic Software Innovation

Part 2: Creating Value through Software DevelopmentInternational audienceWe understand software innovation as concerned with introducing innovation into the development of software intensive systems, i.e. systems in which software development and/or integration are dominant considerations. Innovation is key in almost any strategy for competitiveness in existing markets, for creating new markets, or for curbing rising public expenses, and software intensive systems are core elements in most such strategies. Software innovation therefore is vital for about every sector of the economy. Changes in software technologies over the last decades have opened up for experimentation, learning, and flexibility in ongoing software projects, but how can this change be used to facilitate software innovation? How can a team systematically identify and pursue opportunities to create added value in ongoing projects? In this paper, we describe Deweyan pragmatism as the philosophical foundation for Essence – a software innovation methodology – where unknown options and needs emerge as part of the development process itself. The foundation is illustrated via a simple example

Developing Theory Through Integrating Human and Machine Pattern Recognition

New forms of digital trace data are becoming ubiquitous. Traditional methods of qualitative research that aim at developing theory, however, are often overwhelmed by the sheer volume of such data. To remedy this situation, qualitative researchers can engage not only with digital traces, but also with computational tools that are increasingly able to model digital trace data in ways that support the process of developing theory. To facilitate such research, this paper crafts a research design framework based on the philosophical tradition of pragmatism, which provides intellectual tools for dealing with multifaceted digital trace data, and offers an abductive analysis approach suitable for leveraging both human and machine pattern recognition. This framework provides opportunities for researchers to engage with digital traces and computational tools in a way that is sensitive to qualitative researchers’ concerns about theory development. The paper concludes by showing how this framework puts human imaginative capacities at the center of the push for qualitative researchers to engage with computational tools and digital trace